Foundations of Data Science
Bayesian Information Criterion (BIC) is a statistical measure used to compare the goodness of fit of different models while penalizing for the number of parameters to avoid overfitting. It helps determine which model among a set of models is more likely to be the true model based on the data. A lower BIC value indicates a better model, making it particularly useful in multiple linear regression for selecting the optimal subset of predictors.
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